Pixhawk controlled quadcopter: enabling autonomous surveillance using telemetry for effective monitoring K. K. Deepika, P. Sai Rohan, S. Dileep Kumar, S. Khwaja Moinuddin, Pavani, R. S. Ravi Sankar Advances in Electronics Computer Physical and Chemical Sciences, 2025 The use of self-navigating surveillance drones that have been programmed to follow different routes has shown considerable improvements in surveillance capabilities. The performance of these drones was assessed in this study, and significant results were found. With a speed of 9.82 m/s, the unmanned aerial vehicles (UAVs) demonstrated its ability to operate quickly and effectively. Test path analysis revealed very few differences when compared to manual operations, taking an average of two minutes to complete the path. Furthermore, in autopilot mode, the Pixhawk flight controller demonstrated better stabilization. The RTL interruption test revealed a path spline deviation that altered the UAV’s return-to-launch trajectory. These findings highlight how autonomous surveillance drones can improve operational effectiveness and surveillance coverage. Because flexibility in different paths is provided, it is possible to thoroughly scan large areas in a short amount of time, optimizing the effectiveness of surveillance. Adaptive path-following and real-time data transmission improve operational dependability and situational awareness even more. As a result, autonomous surveillance drones offer a flexible and affordable option for a range of uses, such as emergency response, infrastructure monitoring, and border security. All things considered, the incorporation of autonomous surveillance drones with a variety of paths represents a major advancement in surveillance technology, providing unmatched capacity for productive and successful monitoring in a range of operational scenarios.
Design of Total Harmonic Distortion Reduction Using Quantum Coyote Optimization Algorithm for Hybrid Power Generation Systems Lijo Jacob Varghese, R. Gandhi Raj, R. S. Ravi Sankar, Zhenhai Tan Journal of Circuits Systems and Computers, 2023 The usage of various inverters in various industries has gained considerable attention in the power electronics industry in recent years. The harmonic distortion that is induced by various renewable energy sources, along with the growing use of nonlinear loads and power electronic devices, has a significant impact on the distribution system. This is because of the rise in penetration of various renewable energy sources and the usage of nonlinear loads and power electronic devices. In addition, distributed generation (DG) units with inverters (such as solar (PV) and wind turbines) that are integrated into distribution networks are viewed as significant harmonic producers that have substantial adverse effects on power quality. The power quality in the system suffers because of these generators. This study proposes a method of harmonic mitigation for addressing power quality problems that are present in distribution systems as a solution to the challenges that have been found. These concerns have been brought to light as a result of previous research. The standard two-level and three-level inverters were the basis for the development of the multilevel inverter (MLI), which was meant to address their shortcomings. One of the effective technologies that can maintain constant performance is the hybrid power generating system. A hybrid energy system has several benefits, including high dependability, cheap cost and minimal emissions. When used in a hybrid power production system, the reduction of total harmonic distortion (THD) becomes absolutely necessary (HPGS). In this context, the research provides a novel approach for high-performance quantum computing called quantum coyote optimization algorithm-based THD reduction (QCOA-THDR). The QCOA-THDR approach that has been presented has been tested with several converters, including SEPIC, buck–boost and Cuk converters. Additionally, the proportional as well as the integral gain variables of the proportional integral (PI) controller are set in order to achieve decreased total harmonic distortion (THD). In addition, the QCOA system is formed by combining the ideas of quantum computing (QC) with the traditional COA. This is how the QCOA system comes to exist. A limited number of simulations were run, and the results are being analyzed from a variety of perspectives in order to investigate the improved effects that the QCOA-THDR approach has on data. The QCOA-THDR method was shown to have superior results than the more modern techniques, as shown by the comparison research.
A Smart ANN-Based Converter for Efficient Bidirectional Power Flow in Hybrid Electric Vehicles R.S.Ravi Sankar, Keerthi Deepika.K, Mohammad Alsharef, Basem Alamri Electronics Switzerland, 2022 Electric vehicles (EV) are promising alternate fuel technologies to curtail vehicular emissions. A modeling framework in a hybrid electric vehicle system with a joint analysis of EV in powering and regenerative braking mode is introduced. Bidirectional DC–DC converters (BDC) are important for widespread voltage matching and effective for recovery of feedback energy. BDC connects the first voltage source (FVS) and second voltage source (SVS), and a DC-bus voltage at various levels is implemented. The main objectives of this work are coordinated control of the DC energy sources of various voltage levels, independent power flow between both the energy sources, and regulation of current flow from the DC-bus to the voltage sources. Optimization of the feedback control in the converter circuit of HEV is designed using an artificial neural network (ANN). Applicability of the EV in bidirectional power flow management is demonstrated. Furthermore, the dual-source low-voltage buck/boost mode enables independent power flow management between the two sources—FVS and SVS. In both modes of operation of the converter, drive performance with an ANN is compared with a conventional proportional–integral control. Simulations executed in MATLAB/Simulink demonstrate low steady-state error, peak overshoot, and settling time with the ANN controller.
Energy Efficient Photovoltaic-Electric Spring for Real and Reactive Power Control in Demand-Side Management Keerthi Deepika Kollipara, J. Vijay Kumar, Prasanthi R, Srinivasa Rao Sura, M. S. Pradeep Kumar Patnaik, R. S. Ravi Sankar Frontiers in Energy Research, 2022 Photovoltaic-electric spring (PV-ES) is a promising topology to utilize widespread residential roof-top photovoltaic systems in demand-side management. Power control for an integrated configuration of photovoltaic-electric spring system to achieve dynamic supply-demand balance in power distribution networks is presented. Extraction of maximum power from PV panel using Perturb and Observe algorithm along with boost converter are designed. This power is given as input to the DC link of the Electric Spring. The modeling and design of the integrated system are detailed. Extensive simulations are carried out in MATLAB/Simulink to observe the performance of the PV-ES system. The effectiveness of the proposed topology was verified for changes in line voltage, PV irradiation, and reference power. It was confirmed that the proposed PV-ES precisely controls the active power consumption of the critical load, rigidly regulates the voltage at the point of common coupling (PCC), and follows the variations in reference power available for the smart load. Finally, the expansive performance of ES fed with a PV source was confirmed to be superior over an ES system fed with a DC source.
Design of Back-to-Back Converter Interface for Electric Spring in a Distribution System K. K. Deepika, J. Vijaya Kumar, Srinivasa Varma Pinni, Srinivasa Rao Sura, R. S. Ravi Sankar Frontiers in Energy Research, 2022 In a distribution system, the erratic output power of distributed generation causes fluctuations in the available power to critical loads on the demand side. A novel electric spring (ES) with back-to-back converter configuration is proposed. Besides PCC voltage regulation and power control, the proposed converter integrates the ES to the grid without compromising the DC link voltage and the quality of the grid current. It comprises an instantaneous DC link voltage control, active power control, PCC voltage control, and a hysteresis band current control. The systematic design of the parameters in the configuration is detailed. Simulations were performed in MATLAB/Simulink, and a series of comparative analyses at various control stages were demonstrated. The quality of the grid current was analyzed with PI, PR, and hysteresis band current controllers. It was established that the hysteresis band current controller gave the best performance. Similarly, the DC link voltage was efficiently regulated with the instantaneous DC link voltage controller than the conventional controller.
A Novel Anomaly Detection Method in Sensor Based Cyber-Physical Systems K. Muthulakshmi, N. Krishnaraj, R. S. Ravi Sankar, A. Balakumar, S. Kanimozhi, B. Kiruthika Intelligent Automation and Soft Computing, 2022 In recent times, Cyber-physical system (CPS) integrates the cyber systems and physical world for performing critical processes that are started from the development in digital electronics. The sensors deployed in CPS are commonly employed for monitoring and controlling processes that are susceptible to anomalies. For identifying and detecting anomalies, an effective anomaly detection system (ADS) is developed. But ADS faces high false alarms and miss detection rate, which led to the degraded performance in CPS applications. This study develops a novel deep learning (DL) approach for anomaly detection in sensor-based CPS using Bidirectional Long Short Term Memory with Red Deer Algorithm (BiLSTM-RDA). The presented BiLSTM-RDA model comprises preprocessing classification, and parameter tuning. Initially, the sensor data undergoes preprocessing to remove the noise present in it. Afterward, the BiLSTM based classification process takes to detect the existence of anomalies in CPS. At last, parameter tuning of the Bi-LSTM model is carried out by the use of RDA for tuning the parameters such as the number of hidden layers, batch size, epoch count, and learning rate. For assessing the experimental outcome of the BiLSTM-RDA technique, a comprehensive experimentation is performed using the data from sensor-based CPS. A detailed comparative analysis takes place to ensure the effective detection performance of the BiLSTM-RDA model and The obtained experimental results verified the superior performance on the applied data over the compared methods with the maximum an average precision of 0.989, recall of 0.984, F-score of 0.985, and accuracy of 0.983.
Adaptive hysteresis band current control of grid connected PV inverter R. S. Ravi Sankar, A. Venkatesh, Deepika Kollipara International Journal of Electrical and Computer Engineering, 2021 In this paper, adaptive hysteresis band current controller is implemented to control the current injected into the grid. Initially it was implemented by B.K Bose for control of the machine drive. Now it is implemented for the grid connected PV inverter, to control the current injected into Grid. It is well suitable for the distribution generation. The adaptive hysteresis band controller changes the bandwidth based on the modulating frequency, supply voltage, input DC voltage and slope of the reference current. Consequently, the controller generates pulses to the inverter. It is advantageous over the conventional hysteresis controller, as the switching frequency is maintained almost constant. Thereby quality of grid current is also improved. It is verified in time domain analysis of simulation using MATLAB.
Harmonic stability analysis of multi-paralleled 3-phase pv inverters tied to grid R. S. Ravi Sankar, K. K. Deepika, A. V. Satyanarayana International Journal of Power Electronics and Drive Systems, 2021 In this paper the harmonic stability is investigated for multi paralleled three-phase photovoltaic inverters connected to grid. The causes to harmonically stabilize/destabilize the multi-paralleled PV inverters when tied to the grid isanalysed by the impedance-based stability criterion (IBSC). In this paper stability of the system is investigated by varying the grid inductance with constant grid resistance and also by varying load impedance while maintaining grid inductance constant. Stability of the multiple three phase inverters tied to the grid with different grid impedance, inductance value inparticular are analyzed. Overall system is stable up to grid inductance of5mH even though there is change in load admittance. It is concluded that system stability depends only on grid impedance. It is verified with Matlab Simulations.
